Mining interaction patterns in coarse trajectory data sets

Authors: Somayeh Dodge*, University of Minnesota, Jasper Johnson, University of Minnesota, Sean Ahearn, CUNY- Hunter College
Topics: Geographic Information Science and Systems
Keywords: time-geography, trajectory analysis, movement, interaction
Session Type: Paper
Day: 4/5/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Washington 6, Marriott, Exhibition Level
Presentation File: No File Uploaded

Interaction between moving individuals happens at multiple spatial and temporal scales. Direct interaction occurs when two individuals are at the spatial proximity of each other at the same time window. Indirect (or delayed) interaction happens when individuals interact in the same location with a time delay. For instance, a tiger can pick up the scent from other tigers after multiple days and follow their path. Or people may contract infectious diseases when they move through areas that were previously infected with a virus (like in Ebola or Zika cases) or when they cross-path other sick individuals directly or with a delay (like in Flu cases). The challenge is how to identify interaction when fine resolution tracking data are not available. This research presents an approach to identify direct and indirect interaction patterns in movement data sets obtained from GPS tracking of multiple individuals. The aim is to quantify interaction in space and time, and present a methodology to extract patterns of interaction from coarse trajectory data sets.

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